Overview

Data Structures
Divisions Metrics Values
size observations 70
size variables 9
size values 630
size memory size (KB) 0
duplicated duplicate observation 0
missing complete observation 70
missing missing observation 0
missing missing variables 0
missing missing values 0
Data Types
Divisions Metrics Values
data type numerics 2
data type integers 4
data type factors/ordered 0
data type characters 3
data type Dates 0
data type POSIXcts 0
data type others 0
Job Informations
Divisions Metrics Values
dataset dataset base
dataset dataset type tbl_df
dataset target W
job samples 70 / 70 (100%)
job created 2023-11-23 22:28:52.213793
job created by dlookr






Univariate Analysis

Descriptive Statistics

Descriptive statistics and visualization of individual variables
Variables
Missing (%)
Distincts (Ratio)
Zeros
Negatives
Outliers
​
Tm
character
0
(0)
5
(0.071)
-
-
-
​
W
integer
0
(0)
47
(0.671)
0
0
0
​
L
integer
0
(0)
47
(0.671)
0
0
0
​
W-L%
numeric
0
(0)
55
(0.786)
0
0
0
​
GB
character
0
(0)
39
(0.557)
-
-
-
​
RS
integer
0
(0)
69
(0.986)
0
0
0
​
RA
integer
0
(0)
68
(0.971)
0
0
0
​
pythW-L%
numeric
0
(0)
61
(0.871)
0
0
0
​
Date
character
0
(0)
14
(0.2)
-
-
-


Normality Test

Normality test results of numeric variables
Variables
Mean
Min
Q1
Median
Q3
Max
Balance
​
W
52.49
7
29
54
73.75
104
Balanced
​
L
49.39
7
29
48.5
71
107
Balanced
​
W-L%
0.51
0.304
0.43825
0.5205
0.59725
0.682
Balanced
​
RS
457.67
80
253.25
467
649
947
Balanced
​
RA
449.99
65
268.75
450.5
647.5
855
Balanced
​
pythW-L%
0.5
0.332
0.43125
0.4935
0.5735
0.679
Balanced


Bivariate Analysis

Compare Numerical Variables

Relationship between two numerical variables
First Variable
Second Variable
Correlation Coefficient
​
W
L
0.67807
​
W
W-L%
0.38646
​
W
RS
0.97590
​
W
RA
0.82041
​
W
pythW-L%
0.36927
​
L
W-L%
-0.32274
​
L
RS
0.77335
​
L
RA
0.96170
​
L
pythW-L%
-0.30497
​
W-L%
RS
0.24427
1–10 of 15 rows


Compare Categorical Variables

The number of categorical variables is less than 2.


Multivariate Analysis

Correlation Analysis

Correlation Matrix

Correlation coefficient matrix of numeric variables
​
Second Variable
First Variable
W
L
W-L%
RS
RA
pythW-L%
W
​
0.678
0.386
0.976
0.820
0.369
L
0.678
​
-0.323
0.773
0.962
-0.305
W-L%
0.386
-0.323
​
0.244
-0.125
0.914
RS
0.976
0.773
0.244
​
0.900
0.258
RA
0.820
0.962
-0.125
0.900
​
-0.135
pythW-L%
0.369
-0.305
0.914
0.258
-0.135
​


Correlation Plot

Correlation coefficient matrix plot


Target based Analysis

Target Variable and Numeric Variables

Relationship between two numerical variables by level of target variable
Variable
Target Variable
​
L
W
Visuzlization of relation
Statistics
Values
Residual standard error
20.6161224
Degrees of freedom
68
Multiple R-squared
0.4597767
Adjusted R-squared
0.4518323
F-statistic
57.8738863
p-value
0
Estimate
Std. Error
t value
Pr(>|t|)
(Intercept)
16.3227878
5.3542928
3.0485423
0.0032744
L
0.7322548
0.0962545
7.6074888
0.0000000
​
W-L%
W
​
RS
W
Visuzlization of relation
Statistics
Values
Residual standard error
6.1213435
Degrees of freedom
68
Multiple R-squared
0.952373
Adjusted R-squared
0.9516726
F-statistic
1359.7629376
p-value
0
Estimate
Std. Error
t value
Pr(>|t|)
(Intercept)
-0.3707923
1.6093254
-0.2304023
0.8184709
RS
0.1154901
0.0031319
36.8749636
0.0000000
​
RA
W
​
pythW-L%
W


Target Variable and Categorical Variables

There are no categorical variables except for the target variable.



 

Created by dlookr package